Пакунок: r-bioc-gsva (1.46.0+ds-1)

[ Source: r-bioc-gsva  ]

Gene Set Variation Analysis for microarray and RNA-seq data

Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene- set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross- tissue pathway analysis, in a pathway-centric manner.

Інші пакунки пов'язані з r-bioc-gsva

• dep: libc6 (>= 2.17) [arm64, ppc64el]

  Бібліотека GNU C: спільні бібліотеки
  also a virtual package provided by libc6-udeb

  dep: libc6 (>= 2.4) [not arm64, ppc64el]

• dep: r-api-4.0

  virtual package provided by r-base-core

• dep: r-api-bioc-3.16

  virtual package provided by r-bioc-biocgenerics

• dep: r-base-core (>= 4.2.2.20221110-1)

  GNU R core of statistical computation and graphics system

• dep: r-bioc-biobase

  base functions for Bioconductor

• dep: r-bioc-biocparallel

  BioConductor facilities for parallel evaluation

• dep: r-bioc-biocsingular

  Singular Value Decomposition for Bioconductor Packages

• dep: r-bioc-delayedarray

  BioConductor delayed operations on array-like objects

• dep: r-bioc-delayedmatrixstats

  Functions on Rows and Columns of 'DelayedMatrix' Objects

• dep: r-bioc-gseabase

  Gene set enrichment data structures and methods

• dep: r-bioc-hdf5array

  HDF5 backend for DelayedArray objects

• dep: r-bioc-iranges

  GNU R low-level containers for storing sets of integer ranges

• dep: r-bioc-s4vectors

  BioConductor S4 implementation of vectors and lists

• dep: r-bioc-singlecellexperiment

  S4 Classes for Single Cell Data

• dep: r-bioc-sparsematrixstats

  BioConductor summary statistics for rows and columns of sparse matrices

• dep: r-bioc-summarizedexperiment

  BioConductor assay container

• dep: r-cran-matrix (>= 1.5-0)

  GNU R package of classes for dense and sparse matrices

• rec: r-cran-fastmatch

  GNU R package for fast match replacement for repeated look-ups

• rec: r-cran-runit

  GNU R package providing unit testing framework

• sug: r-bioc-biocgenerics

  generic functions for Bioconductor

• sug: r-bioc-biocstyle

  standard styles for vignettes and other Bioconductor documents

• sug: r-bioc-edger

  Empirical analysis of digital gene expression data in R

• sug: r-bioc-genefilter

  methods for filtering genes from microarray experiments

• sug: r-bioc-limma

  linear models for microarray data

• sug: r-bioc-org.hs.eg.db

  genome-wide annotation for Human

• sug: r-cran-data.table

  GNU R extension of Data.frame

• sug: r-cran-future

  R package: A Future API for R

• sug: r-cran-ggplot2

  implementation of the Grammar of Graphics

• sug: r-cran-knitr

  GNU R package for dynamic report generation using Literate Programming

• sug: r-cran-plotly

  create interactive web graphics via 'plotly.js' in GNU R

• sug: r-cran-promises

  GNU R abstractions for promise-based asynchronous programming

• sug: r-cran-rcolorbrewer

  GNU R package providing suitable color palettes

• sug: r-cran-rmarkdown

  convert R markdown documents into a variety of formats

• sug: r-cran-shiny

  GNU R web application framework

• sug: r-cran-shinydashboard

  GNU R create dashboards with 'Shiny'

• sug: r-cran-shinyjs

  Easily Improve the User Experience of Your Shiny Apps in Seconds

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Архітектура	Розмір пакунка	Розмір після встановлення	Файли
amd64	781.2 kB	912.0 kB	[список файлів]
arm64	786.6 kB	964.0 kB	[список файлів]
armel	782.3 kB	963.0 kB	[список файлів]
armhf	780.7 kB	963.0 kB	[список файлів]
i386	781.3 kB	911.0 kB	[список файлів]
mips64el	788.0 kB	964.0 kB	[список файлів]
mipsel	781.2 kB	963.0 kB	[список файлів]
ppc64el	782.4 kB	964.0 kB	[список файлів]
s390x	781.0 kB	908.0 kB	[список файлів]